Research output per year
Research output per year
Personal profile
Research interests
Dr Thomas Day is a Clinical Research Fellow working as part of the Intelligent Fetal Imaging and Diagnosis (iFIND) project. He is a Paediatric and Fetal Cardiologist, and undertakes clinical work at The Evelina London Children's Hospital, part of Guy's and St Thomas' NHS Foundation Trust. His research interest is the use of artificial intelligence to improve screening for congenital heart disease.
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Education/Academic qualification
Medicine, Master of Research, MRes (intercalated), University of Manchester
2006 → 2008
Award Date: 1 Jun 2008
Medicine, Bachelor of Medicine, MBChB, University of Manchester
2002 → 2008
Award Date: 1 Jun 2008
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Interaction between clinicians and artificial intelligence to detect fetal atrioventricular septal defects on ultrasound: how can we optimize collaborative performance?
Day, T. G., Matthew, J., Budd, S. F., Venturini, L., Wright, R., Farruggia, A., Vigneswaran, T. V., Zidere, V., Hajnal, J. V., Razavi, R., Simpson, J. M. & Kainz, B., Jul 2024, In: Ultrasound in Obstetrics and Gynecology. 64, 1, p. 28-35 8 p.Research output: Contribution to journal › Article › peer-review
Open Access1 Citation (Scopus) -
Feature-Conditioned Cascaded Video Diffusion Models for Precise Echocardiogram Synthesis
Reynaud, H., Qiao, M., Dombrowski, M., Day, T., Razavi, R., Gomez, A., Leeson, P. & Kainz, B., 2023, Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 - 26th International Conference, Proceedings. Greenspan, H., Greenspan, H., Madabhushi, A., Mousavi, P., Salcudean, S., Duncan, J., Syeda-Mahmood, T. & Taylor, R. (eds.). Springer Science and Business Media Deutschland GmbH, p. 142-152 11 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 14229 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review
Open Access -
Improving image labelling quality
Day, T. G., Simpson, J. M., Razavi, R. & Kainz, B., Apr 2023, In: Nature Machine Intelligence. 5, 4, p. 335-336 2 p.Research output: Contribution to journal › Comment/debate › peer-review
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Prenatal diagnosis of hypoplastic left heart syndrome on ultrasound using artificial intelligence: How does performance compare to a current screening programme?
Day, T. G., Budd, S., Tan, J., Matthew, J., Skelton, E., Jowett, V., Lloyd, D., Gomez, A., Hajnal, J. V., Razavi, R., Kainz, B. & Simpson, J. M., 2023, (Accepted/In press) In: Prenatal Diagnosis.Research output: Contribution to journal › Article › peer-review
Open Access2 Citations (Scopus) -
RE: Wang et al. Diagnosis of fetal total anomalous pulmonary venous connection based on the post-left atrium space ratio using artificial intelligence
Day, T. G., Kainz, B., Razavi, R. & Simpson, J., Mar 2023, In: Prenatal Diagnosis. 43, 3, p. 400-401 2 p.Research output: Contribution to journal › Letter › peer-review
Projects
- 1 Finished
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Artificial intelligence to improve antenatal detection of congenital heart disease
NIHR National Institute For Health & Care Research
1/04/2021 → 31/03/2024
Project: Research